ArticlePeerJ2026
Microbial diversity and functional analysis in wastewater and sludge of wastewater treatment plants.
Article in PeerJ, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
Background: The efficiency of wastewater treatment plants (WWTPs) relies heavily on microbial communities. However, the microbial characteristics of different treatment units in the Qian'an WWTP (Hebei, China) remain unclear. This study investigates its microbial diversity and functions to provide a basis for process optimization. Methods: Samples were collected in October 2024 from four representative units were selected: sludge (group A), sedimentation tank water (group C), aeration tank water (group E), and raw wastewater (group F). Bacterial and fungal communities were analyzed Results: Bacterial richness was highest in groups A, C, and E and lowest in group F, whereas fungal richness was highest in groups C and E and lowest in group F. The microbial community structures of groups C and E were highly similar in terms of richness and diversity patterns, but both differed markedly from groups A and F. At the phylum level, bacteria in group A were significantly enriched in Chloroflexi and Firmicutes, and fungi by Rozellomycota; bacteria in groups C, E and F were mainly Proteobacteria and Bacteroidetes. Fungal composition varied significantly, with Rozellomycota in A, Blastocladiomycota in C/E, and Ascomycota in F. Predicted Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed 25 differential metabolic pathways ( Conclusions: This study clarifies the microbial characteristics across treatment units and highlights the nitrogen cycling potential of the WWTP microbiome, providing a scientific basis for optimizing treatment processes.
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